Join Our Team

ML Frameworks Team Manager

Our system runs training and inference workloads orders of magnitude faster than contemporary machines, fundamentally changing the way ML researchers work and pursue AI innovation.

We are innovating at every level of the stack – from chip, to microcode, to power delivery and cooling, to new algorithms and network architectures at the cutting edge of ML research. Our fully-integrated system delivers unprecedented performance because it is built from the ground up for deep learning workloads.

Cerebras is building a team of exceptional people to work together on big problems. Join us!

The Team

The Cerebras software platform is designed to be targeted by today’s most relevant machine learning frameworks, such as TensorFlow, PyTorch, Caffe2, and MXNet.

Our ML Framework team is responsible for integrating these frameworks to work with our own highly optimized software stack. This involves creating tools and designing workflows that enable the development, training, and deployment of machine learning models on our new hardware system.

Fundamentally, you will be enabling ML researchers to use the software tools and workflows of today to unlock the advanced hardware capabilities of tomorrow.

The Role

As the manager of Cerebras’s ML Framework team, you will lead, build, and manage a team of highly talented and motivated ML engineers in a fast-paced environment to solve toughest of the problems in rapidly evolving AI space.

Responsibilities include:

Lead the team to develop the framework software connecting representations of existing deep learning frameworks — such as TensorFlow and PyTorch — with our customized back-end;

Understand the runtime environments of existing frameworks and our backend, and lead the technical direction for an execution model connecting them together in a way that is seamless to the user

Driving relationships with the development teams and developer communities of popular ML Frameworks to collaborate on integration needs and future directions

Provide technical guidance to team members in designing, analyzing, and optimizing algorithmic solutions

Work with engineering leadership and product management teams to develop product roadmap

Identify hiring needs and fill them with best talent from universities and industry

Mentor and coach team members considering both short-term execution and long-term career growth needs

Identify risks in product development schedule and take active measures to mitigate them

Actively participate in defining next generation system architecture with hardware and systems teams and provide software perspective for feature prioritization

Define and enforce best practices in software development process including coding style standards and peer reviews

Identify opportunities for deployment of tools and processes to improve engineering execution efficiency